Vehicle fleet managers or administrators manage several drivers and units of equipment when overseeing operation of the vehicles of the fleet. For example, the fleet can have several trucks that can be driven, interchangeably, by several drivers or operators. Systems and modules associated with the vehicles can sense and record observations related to safety, compliance, fuel efficiency, location, and other metrics. The observations and data can be collected by in-cab units or computing systems. Further, the vehicle fleet managers or administrators can use the data to manage the fleet, schedule drivers, schedule vehicle maintenance, and perform other tasks.
However, current systems and methods only report the observations and data in the context of a single entity, such as an operator or a vehicle. For example, safety- or fuel-related event observations are associated with vehicles, while compliance-related information is associated with drivers. The current systems cannot switch contexts and view the event observations organized by drivers or vehicles, interchangeably. Therefore, more complex data processing is necessary to correlate the data. Further, the current systems cannot organize the multi-context data on a real-time basis.
A need therefore exists for systems and methods for associating operator- and vehicle-related data. More particularly, a need exists for platforms and techniques for reporting performance data interchangeably by associating operator- and vehicle-related data on a real-time basis.